6 papers
Nash-Bargaining HalpernSGD via Limited-Memory MultiLRSGA: A Two-Phase Optimizer for Multi-Objective Learning
Katherine Rossella Foglia, Francesco Sergio Pisani, Vittorio Colao
We propose NB-HalpernSGD via LM-MultiLRSGA, a two-phase optimizer for multi-objective optimization. The process starts with a competitive optimization phase by applying a limited-m…
MultiLRSGA: A method for multi-player differentiable games
Katherine Rossella Foglia, Vittorio Colao, Alfio Borzì
We propose MultiLRSGA, an -player extension of LRSGA for the computation of stable Nash equilibria in differentiable games. The method originates from the decomposition of the g…
On the Convergence of HalpernSGD
Vittorio Colao, Katherine Rossella Foglia
We study HalpernSGD for minimizing a convex Fréchet differentiable function with Lipschitz gradient on a real Hilbert space. Its deterministic orbit converges strongly to the ancho…
Limited-Memory LRSGA: An Iterative Method for Computing Nash Equilibria in Competitive Optimization Problems
Katherine Rossella Foglia, Francesco Sergio Pisani, Vittorio Colao
We introduce LMLRSGA, a limited memory variant of Low Rank Symplectic Gradient Adjustment (LRSGA) for differentiable games. It is an iterative scheme for approximating Nash equilib…
A Low-Rank Symplectic Gradient Adjustment Method for Computing Nash Equilibria
Nadja Vater, Katherine Rossella Foglia, Vittorio Colao +1
This work presents a theoretical and numerical investigation of the symplectic gradient adjustment (SGA) method and of a low-rank SGA (LRSGA) method for efficiently solving revviol…
On the Rate of Asymptotic Regularity of Iterative Methods for Nonexpansive Mappings in CAT(0) Spaces and Hyperbolic Optimization
Katherine Rossella Foglia, Vittorio Colao
The Krasnosel'ski\uı--Mann and Halpern iterations are classical schemes for approximating fixed points of nonexpansive mappings in Banach spaces, and have been widely studied in mo…